Dynamic spectrum access, or cognitive radio communication, is a technique in which a device monitors radio channels on any potential frequency band for activity, and establishes communications only on an inactive channel. The usage of radio spectrum may therefore be improved in that frequency bands are not exclusively assigned to a particular transmission system, largely based on the observation that spectrum assigned by licenses to licensees is often not used. One approach pursued in regulations is to license the spectrum to a licensee, denoted primary user, while at the same time the frequency band can be used by other users, denoted secondary users, under the condition that they do not interfere too much with the system operation of the primary user.
To ensure that a secondary user do not cause excessive interference, that harms the communication of the primary users of the spectrum, spectrum sensing can be employed. Spectrum sensing means that the secondary user, alone or cooperatively together with other secondary users, uses detection mechanisms to determine if a primary transmission is present in the spectrum or not. One common and simple method for spectrum sensing is energy detection, where the secondary user measures the received energy on a frequency band and compares the result with a threshold. If the received energy is above the threshold the user decides that a primary transmission is taking place and hence the secondary user should refrain from transmissions on that band until it can be established that there are no longer any primary transmissions present. On the other hand if the received energy falls below the threshold secondary user assumes that the frequency band is free, implying that the secondary user may use it for its own transmissions.
Many variants and methods for spectrum sensing have been proposed in the research literature over the years and the above simple energy detection scheme is just one of these. There exist a multitude of different methods for spectrum sensing in the literature. Some are specific to very specific types or signals, or signals with certain properties, such as matched filtering approaches or cyclostationary detection methods. Others are more general, e.g., energy detection or eigenvalue distribution based methods. The former set of methods can typically be used for detection of a particular system of interest, e.g., a specific primary user system, whereas the latter set of methods can typically be used when the other potentially present systems are unknown or if less specific knowledge of the radio environment is required. A comprehensive summary of spectrum sensing methods is disclosed in e.g., [Erik Axell, “Topics in Spectrum Sensing for Cognitive Radio”, Linköping Studies in Science and Technology, Licentiate Thesis no 1417, 2009.].
Generally, for all detection methods, the noise level should be as low as possible. By “noise” one here means “everything in the received signal which does not originate from what one wishes to detect”, e.g., any contribution to the signal which does not originate from a primary user. For this reason it has been proposed in various forums that quiet periods should be introduced in a wireless system that opportunistically accesses the spectrum to allow the spectrum sensing mechanisms to detect the potential primary user transmissions. This feature is implemented, e.g., in the IEEE 802.22 standard.
In short; spectrum sensing for primary usage detection benefits from quiet periods.
From the patent application publication WO/2009/069069, titled “DISTRIBUTED SCHEDULING OF QUIET-PERIOD FOR IN-SERVICE CHANNEL MONITORING”, is earlier known a system using spectrum sensing for primary usage detection. However, the system is only for intra system use only. Every user equipment reports required lengths of sensing periods and the total system adapts the quiet period to the longest demand. Techniques are also provided for efficient coordination of on-demand quiet-period requests, and for supporting different quiet-period schedules for multiple classes of primary users.
The main drawback with the existing solutions is that they only consider quiet periods in one system. However, if several different secondary systems employ spectrum sensing in the same spatial region to detect the primary users, said secondary systems may falsely detect each other as a primary user that needs to be protected. This is not what is intended with the introduction of quiet periods, since the access of spectrum opportunistically in a secondary manner is often supposed to be on equal terms between the present secondary users. This means that no secondary transmission should have priority over and be more protected than any other secondary transmission. Further, even if good detection methods specific to the primary system are available, the presence of secondary transmissions will increase the noise level, with the above definition of noise, and make primary user detection more difficult. To conclude, intra-system quiet period synchronization is beneficial for sensing, but does not solve the problem with interference between different secondary systems.